WO2010150198A2 - Procédé et dispositif pour une estimation de canal améliorée dans des systèmes de communication sans fil - Google Patents

Procédé et dispositif pour une estimation de canal améliorée dans des systèmes de communication sans fil Download PDF

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Publication number
WO2010150198A2
WO2010150198A2 PCT/IB2010/052835 IB2010052835W WO2010150198A2 WO 2010150198 A2 WO2010150198 A2 WO 2010150198A2 IB 2010052835 W IB2010052835 W IB 2010052835W WO 2010150198 A2 WO2010150198 A2 WO 2010150198A2
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WO
WIPO (PCT)
Prior art keywords
channel
channel estimates
estimates
generating
statistics
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Application number
PCT/IB2010/052835
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English (en)
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WO2010150198A3 (fr
Inventor
Leonid Krasny
Jiann-Ching Guey
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Telefonaktiebolaget L M Ericsson (Publ)
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Application filed by Telefonaktiebolaget L M Ericsson (Publ) filed Critical Telefonaktiebolaget L M Ericsson (Publ)
Priority to EP10733042.5A priority Critical patent/EP2446596B1/fr
Priority to CN201080028994.8A priority patent/CN102804719B/zh
Publication of WO2010150198A2 publication Critical patent/WO2010150198A2/fr
Publication of WO2010150198A3 publication Critical patent/WO2010150198A3/fr

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/0224—Channel estimation using sounding signals
    • H04L25/0228—Channel estimation using sounding signals with direct estimation from sounding signals
    • H04L25/023—Channel estimation using sounding signals with direct estimation from sounding signals with extension to other symbols
    • H04L25/0232—Channel estimation using sounding signals with direct estimation from sounding signals with extension to other symbols by interpolation between sounding signals
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/0212—Channel estimation of impulse response
    • H04L25/0218—Channel estimation of impulse response with detection of nulls
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/022—Channel estimation of frequency response
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/024—Channel estimation channel estimation algorithms
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L5/00—Arrangements affording multiple use of the transmission path
    • H04L5/0001—Arrangements for dividing the transmission path
    • H04L5/0003—Two-dimensional division
    • H04L5/0005—Time-frequency
    • H04L5/0007—Time-frequency the frequencies being orthogonal, e.g. OFDM(A), DMT
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L5/00—Arrangements affording multiple use of the transmission path
    • H04L5/003—Arrangements for allocating sub-channels of the transmission path
    • H04L5/0048—Allocation of pilot signals, i.e. of signals known to the receiver

Definitions

  • the present invention generally relates to wireless communications, and particularly relates to generating channel estimates in a wireless communication receiver.
  • Wireless communication receivers estimate propagation channel characteristics and use the estimates to compensate received signals for channel-induced distortion. More advanced receiver types base interference suppression processing on accurate channel estimation. However, generating accurate channel estimates is challenging, particularly with the growing complexity of communication signal structures.
  • MIMO Multiple-Input-M ⁇ ltiple-Output
  • the transmitter transmits a number of known (or pre-determined) symbols from each transmit antenna, thereby allowing estimation of the MLMO channel by the receiver.
  • the LTE standards as developed by the Third Generation Partnership Project (3GPP). use pilot-assisted channel estimation.
  • LTE uses an Orthogonal Frequency Division Multiplex (OFDM) carrier signal comprising a plurality of narrowband sub-carriers spanning an overall OFDM bandxvidih. Resource allocations assign particular frequencies (sub-carriers) at particular times.
  • OFDM signal "chunk" may be defined as a block of N f consecutive OFDM symbols (along the time axis) and N f consecutive sub-carriers (along the frequency axis).
  • a simplifying assumption is that the channel does not change in time over one chunk and therefore all the pilot symbols are placed in the fust OFDM symbols of the chunk.
  • the goaJ of the channel estimation is to find the estimate of the MIMO channels based on observations of and a priori knowledge of the transmitted pilot symbols
  • One approach is to use Maximum A Posteriori
  • MAP channel estimation Assuming that MIMO channels have Gaussian distribution, it has been shown that MAP channel estimation algorithm can be expressed as
  • ⁇ are the elements of the matrix which is inverse to the matrix Ay with elements and is the correlation matrix of the channel in frequency domain. From these expressions, one sees that the MAP-based approach relies on knowledge of second- order channel statistics;, including ihe channel correlation matrix , and the noise spectral density
  • the ML channel estimation algorithm can be expressed as where L is the number of channel taps. N is the number of received samples in time domain, and P are respectively Fourier transforms of the received signal and pilots ; at time is a sampling interval), and are the elements of the matrix which is inverse to the matrix F ; with elements
  • ML estimation is simpler to implement in some respects than MAP- based estimators — e.g., ML estimation does not require a priori knowledge of channel statistics, as does MAP estimation ML estimation can yield poor results in some circumstances. For example, ML estimation does not perform particularly well for
  • This document discloses a method and apparatus for channel estimation based on extracting channel information, including noise spectral density, from a received signal, and advantageously exploiting that information for improved channel estimation accuracy.
  • One embodiment is directed to a method of generating channel estimates in a wireless communication receiver, for processing a received communication signal
  • the disclosed method includes generating first channel estimates from a set of pilot observations obtained from the received communication signal, using a first channel estimation process not dependent on knowledge of channel statistics.
  • the method further includes estimating channel statistics and a noise variance from the first channel estimates, and generating second channel estimates from the set of pilot observations, the estimated channel statistics, and the estimated noise variance, using a second channel estimation process dependent on knowledge of the channel statistics.
  • one or more embodiments of the above described method include generating revised estimates of the channel statistics and noise variance from the second channel estimates, and generating revised second channel estimates from the set of pilot observations, the revised estimated channel statistics, and the revised estimated noise variance. Iterations beyond this second round of refinements also may be used, where the improved statistical estimations from a preceding iteration are used to improve channel estimation in a succeeding iteration.
  • the receiver circuit includes first and second channel estimators, and a statistical estimator.
  • the first channel estimator is configured to generate first channel estimates from a set of pilot observations obtained from a received communication signal, using a first channel estimation process not dependent on knowledge of channel statistics, and the statistical estimator is configured to estimate channel statistics and a noise variance from the first channel estimates.
  • the second channel estimator is configured to generate second channel estimates from the set of pilot observations, the estimated channel statistics, and the estimated noise variance.
  • the second channel estimator uses a second channel estimation process that is dependent on knowledge of the channel statistics.
  • This example receiver embodiment, and the earlier method example thus may be understood as running two channel estimation processes, where the first process does not require knowledge of the channel statistics, and the second one does. More particularly, in at least one embodiment, the second channel estimation process is known or expected to provide superior channel estimation accuracy as compared to the first channel estimation process, under at least some conditions. The first channel estimation process, however, is sufficiently good to bootstrap or otherwise seed the second process with requisite statistical information.
  • Fig. 2 is a logic flow diagram for one embodiment of a method of channel estimation.
  • Fig. 3 is a block diagram of one embodiment of a receiver circuit configured for channel estimation.
  • Fig. 4 is a flow diagram illustrating one embodiment of time domain and frequency domain processing operations, for channel estimation as proposed herein for an OFDM received signal.
  • Fig. 5 is a performance diagram plotting codeword error rates for channel estimation based on perfect channel knowledge (idealized), based on ML estimation, and based on one embodiment of the estimation proposed herein.
  • Fig. 6 is a table illustrating models and parameters associated with the plot of
  • Fig. ! is a simplified illustration of one embodiment of a wireless communication network 10. which includes a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and a Radio Access Network (RAN) 12 and
  • Core Network (CN) 14 which may be coupled to one or more external networks 16.
  • the CN 14 may couple directly or indirectly to the Internet and/or to other data networks.
  • the RAN 12 includes a number of base stations 20 — one is shown tor simplicity— each having one or more transmit antennas 22, for transmitting radiofrequency signals to and receiving radiofrequency signals from mobile terminals 30 one is shown for simplicity.
  • the signals are propagated over the air, and thus pass through one or more propagation channels.
  • the propagation channels) typically are multipath, and, for MIMO implementations involving multi-antenna transmission and reception, there may be a number of propagation channels involved, corresponding to the different transmit/receive antenna pairings.
  • the illustrated embodiment of the mobile terminal 30 includes one or more transmit/receive antennas 32, which are coupled through antenna interface circuitry 34 to a transmit circuit 36, and a receiver front-end circuit 38.
  • Baseband processing circuits 40 provide signal processing and control functions for the transmitter and receiver front-end circuits 36 and 38, and may be implemented, for example, using one or more microprocessors, digital signal processors, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays, or other digital processing circuitry.
  • ASICs Application Specific Integrated Circuits
  • FPGAs Field Programmable Gate Arrays
  • the processing circuits 40 include a receiver circuit 42 for generating channel estimates, for processing a received communication signal in a wireless communication receiver, e.g., the mobile terminal 30.
  • a receiver circuit 42 for generating channel estimates, for processing a received communication signal in a wireless communication receiver, e.g., the mobile terminal 30.
  • Such circuitry may be pre-programmed or may operate according to stored program instructions, which are maintained in a computer-readable medium within the mobile terminal 30 — e.g., nonvolatile FLASH memory or EEPROM.
  • the receiver circuit 42 is configured to implement a method of generating channel estimates, for processing a received communication signal.
  • the method includes generating first channel estimates from a set of pilot observations obtained from the received communication signal, using a first channel esrimarion process not dependent on knowledge of channei statistics, and estimating channel statistics and a noise variance from the first channel estimates.
  • the method further includes generating second channel estimates from the set of pilot observations, the estimated channel statistics, and the estimated noise variance, using a second channel estimation process dependent on knowledge of the channel statistics.
  • the receiver circuit 42 comprises, for example, signal processing circuitry that is configured to carry out channel estimation processing as proposed herein, within the mobile terminal 30.
  • the base station 20 also includes (RF) transceiver circuits and associated signal processing and control circuits.
  • RF radio frequency
  • Fig. 3 depicts an embodiment of the receiver circuit 42 in more detail.
  • the illustrated circuitry comprises a first channel estimator 50, a statistics estimator 52, and a second channel estimator 54.
  • the first channel estimator 50 is configured to generate first channel estimates from a set of pilot observations obtained from a received communication signal, using a first channel estimation process not dependent on knowledge of channel statistics.
  • the statistical estimator 52 is configured to estimate channel statistics and a noise variance — which may be expressed as a noise spectral density from the first channel estimates.
  • the second channel estimator 54 is configured to generate second channel estimates from the set of pilot observations, the estimated channel statistics, and the estimated noise variance, using a second channel estimation process dependent on knowledge of the channel statistics.
  • the first channel estimator 50 is configured to generate the first channel estimates in a Maximum Likelihood (ML) estimation process, or in a Least Squares Estimation (LSE) process, based on the set of pilot observations and corresponding known nominal pilot symbol values.
  • ML and LSE estimation processes do not require a priori knowledge of the channel statistics and noise variance, and thus provide an advantageous basis for initially processing the pilot observations to obtain initial (first) channel estimates.
  • the second channei estimation process is a Bayesian estimation process that is dependent on a priori statistical knowledge of the channel.
  • the second channel estimator 54 is configured to generate the second channel estimates in a Maximum a Posteriori (MAP) estimation process, based on the estimated channel statistics and the estimated noise variance obtained from the first channel estimation process, and the set of pilot observations.
  • MAP Maximum a Posteriori
  • the same set of pilot observations for the same received signal e.g., one or more OFDM chunks — is used for two channel estimation processes.
  • the first channel estimation process uses the pilot observations to estimate channel statistics and noise variance, where, for example, the statistical estimator 52 is configured to estimate a frequency-domain channel correlation matrix as the channel statistics.
  • the mobile terminal 30 in one or more embodiments comprises an OFDM receiver (transceiver), and the received communication signal comprises an OFDM signal including a number of pilot symbols at given sub-carrier frequencies within an OFDM frequency band.
  • the pilot observations taken by the terminal 30 correspond to the pilot symbols.
  • the first channel estimator 50 is configured to generate the first channel estimates by determining channel taps — processing delays — at which to generate respective ones of the first channel estimates.
  • the estimator's determination is based on transforming received pilot symbols into the time domain to obtain a set of channel taps, and selecting channel taps in die set that are above a defined strength threshold. That is, a measure of received signal strength, or another indication of signal power at the individual channel laps can be used to select a subset of the channel taps for processing use.
  • the first channel estimator 50 in such embodiments is configured to generate the first channel estimates by translating the pilot observations into the time domain and generating ⁇ ime ⁇ domain channel estimates therefrom, and then translating the time-domain channel estimates back into the frequency domain, to obtain the first channel estimates.
  • the statistical estimator 52 is configured to estimate the channel statistics in the frequency domain, based on the (frequency domain) first channel estimates.
  • the second channel estimator 54 is configured to generate the second channel estimates by computing a linear interpolation filler in the frequency domain. The linear interpolation filter is used to generate the second channel estimates for one or more data sub-carrier frequencies within the OFDM frequency band, which are different than the given sub-carrier frequencies of the pilot symbols.
  • the second channel estimator 54 can generate channel estimates at essentially any arbitrary frequency within a given OFDM frequency band, meaning that it can estimate channel response at sub-carrier frequencies, although those frequencies are different from the pilot sub-carrier frequencies.
  • Fig. 4 illustrates one embodiment of such processing, where the dashed vertical line indicates the division between the frequency domain and the time domain, in terms of the receiver circuit's processing.
  • received pilot values i.e., pilot symbols at given sub-carrier positions within an OFDM chunk are converted into the time domain via, e.g., an Inverse Fast Fourier Transform (IFFT).
  • IFFT Inverse Fast Fourier Transform
  • the receiver circuit 42 selects channel taps within the time domain, and generates time-domain channel estimates for the selected channel taps. These time- domain channel estimates are then transformed back into the frequency domain, e.g., via an FFT.
  • Frequency-domain processing further includes computation of the linear interpolation filter, and use of that filler to generate the second channel estimates (for the OFDM data sub-carriers).
  • the statistical estimator 52 is configured to generate revised estimates of the channel statistics and the noise variance from the second channel estimates. That is, the second channel estimates as output from the second channel estimator 54 are used to refine the receiver circuit's estimation of the channel statistics and noise variance.
  • the second channel estimator 54 is configured to generate revised second channel estimates from the set of pilot observations, the revised estimated channel statistics, and the revised estimated noise variance. Titus, the second channel estimates are used to revise the channel statistics and noise variance estimates, and then those revised estimates are used to generate a revised set of second channel estimates.
  • Various embodiments of the receiver circuit 42 may be configured to perform additional iterations, where the revised second channel estimates from a prior iteration are used to generate improved revised estimates of the channel statistics and noise variance in a next iteration, which in turn are used to generate a revised set of second channel estimates.
  • Such iteration is fixed to a defined number of runs in one embodiment, while another embodiment controls the number of iterations based on one or more criterion, such as the change in revised estimates between iterations.
  • the basic improvement in channel estimation accuracy comes from the use of the first estimation process to gain information about (second order) channel statistics.
  • the first step is performing channel estimation using an estimation process that does not depend on knowledge of the channel statistics.
  • the ML and LSE algorithms are two such examples. Taking ML for example, the channel estimate is transformed to the frequency domain, creating the ML estimate of the channel frequency response: At the next step, the estimate from (Eq. 9) is used to estimate the channel correlation matrix as
  • Fig. 5 illustrates the simulated performance, as compared to performance based on perfect channel knowledge, and performance based on ML channel estimation only.
  • the evaluation considered a MIMO system with two mobile terminals 30 transmitting to two base stations 20 on the uplink.
  • the antennas 22 at both base stations 20 were used to receive and jointly detect the information bits from a first one of the mobile terminals 30.
  • the transmissions from the second mobile terminal 30 creates spatially correlated interference when detecting the bits from the first mobile terminal 30.
  • the correlation between ihe Mh and ihe k-th base stations 20 has the form
  • the noise correlation matrix was estimated using the following algorithm: where when the ML channel estimator was used, and where when the proposed channel estimator was used. That is, one embodiment of the base station 20 used a conventional ML-based channel estimation process, and another embodiment implemented a version of the receiver circuit 42, providing channel estimation as proposed herein.
  • the models and parameters for the full simulation are given in the table shown in Fig. 6.
  • the performance curves shown in Fig. 5 plot the average codeword error rate as a function of the average signal-to- noise ratio (SNR) at the receiver of a first one of the two base stations 20.
  • SNR signal-to- noise ratio

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  • Engineering & Computer Science (AREA)
  • Signal Processing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Power Engineering (AREA)
  • Radio Transmission System (AREA)
  • Mobile Radio Communication Systems (AREA)
  • Monitoring And Testing Of Transmission In General (AREA)

Abstract

La présente invention concerne un procédé et un appareil pour une estimation de canal basée sur l'extraction d'informations de canal, comprenant une densité spectrale de bruit, à partir d'un signal reçu, et exploiter de manière avantageuse ces informations pour une précision d'estimation de canal améliorée. Un mode de réalisation concerne un procédé de génération d'estimations de canal dans un récepteur de communication sans fil, pour traiter un signal de communication reçu. Le procédé comprend la génération de premières estimations de canal à partir d'un ensemble d'observations pilotes obtenues à partir d'un signal de communication reçu, en utilisant un premier processus d'estimation de canal qui ne dépend pas de la connaissance des statistiques du canal. Le procédé comprend en outre l'étape consistant à estimer des statistiques de canal et une variation de bruit à partir des premières estimations de canal et à générer des secondes estimations de canal à partir de l'ensemble des observations pilotes, les statistiques de canal estimées et la variation de bruit estimée, en utilisant un second processus d'estimation de canal qui dépend de la connaissance des statistiques du canal.
PCT/IB2010/052835 2009-06-23 2010-06-22 Procédé et dispositif pour une estimation de canal améliorée dans des systèmes de communication sans fil WO2010150198A2 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
EP10733042.5A EP2446596B1 (fr) 2009-06-23 2010-06-22 Procédé et dispositif pour une estimation de canal améliorée dans des systèmes de communication sans fil
CN201080028994.8A CN102804719B (zh) 2009-06-23 2010-06-22 用于无线通信系统中增强信道估计的方法和设备

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US12/489,924 US8379773B2 (en) 2009-06-23 2009-06-23 Method and apparatus for enhanced channel estimation in wireless communication systems

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WO2010150198A3 WO2010150198A3 (fr) 2011-02-24

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9450786B2 (en) 2014-03-27 2016-09-20 King Fahd University Of Petroleum And Minerals Low-complexity method for estimating impulse-radio UWB wireless channels

Families Citing this family (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101011289B1 (ko) * 2009-08-04 2011-01-28 성균관대학교산학협력단 수신 신호 복조 방법 및 이를 수행하는 장치
CN102158437B (zh) * 2010-02-11 2014-07-02 富士通株式会社 信道频域相关性计算设备及方法
US8855240B2 (en) * 2010-02-12 2014-10-07 Blackberry Limited Channel estimation and data detection in a wireless communication system in the presence of inter-cell interference
US20120224498A1 (en) * 2011-03-04 2012-09-06 Qualcomm Incorporated Bayesian platform for channel estimation
US8605804B2 (en) * 2011-04-13 2013-12-10 Intel Mobile Communications GmbH Method of channel estimation and a channel estimator
US20170019240A1 (en) 2015-07-16 2017-01-19 LGS Innovations LLC Tone based in-phase and quadrature-phase (iq) compensation
TWI607633B (zh) 2016-01-19 2017-12-01 瑞昱半導體股份有限公司 無線通訊之雜訊變異量估測電路與方法
US9641357B1 (en) * 2016-01-22 2017-05-02 Mitsubishi Electric Research Laboratories, Inc. System and method for mmWave channel estimation
TWI738317B (zh) * 2019-05-08 2021-09-01 國立臺灣大學 一種通訊系統及其方法
US11652667B2 (en) * 2020-11-25 2023-05-16 Silicon Laboratories Inc. System and method for detecting of channel conditions and channel estimation in an orthogonal frequency division multiplexing (OFDM) receiver
CN113347125B (zh) * 2021-06-09 2022-10-04 浙江大学 针对mimo-ofdm通信系统的贝叶斯神经网络信道估计方法和装置

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8391413B2 (en) 2003-12-19 2013-03-05 Qualcomm Incorporated Channel estimation for an OFDM communication system with inactive subbands
US7830976B2 (en) * 2004-07-16 2010-11-09 Qualcomm Incorporated Iterative channel and interference estimation with dedicated pilot tones for OFDMA
US7817533B2 (en) * 2006-01-11 2010-10-19 Amicus Wireless Technology Ltd. Device and method for performing channel estimation for OFDM-based signals with variable pilot subcarrier spacing
WO2007103183A2 (fr) * 2006-03-01 2007-09-13 Interdigital Technology Corporation Procédé et appareil destinés à l'estimation d'une voie dans un système de multiplexage par répartition orthogonale de la fréquence
WO2008039026A1 (fr) 2006-09-29 2008-04-03 Samsung Electronics Co., Ltd. Procédé et appareil d'estimation de voie dans un système de communication sans fil ofdm
US8379709B2 (en) * 2008-09-04 2013-02-19 Telefonaktiebolaget L M Ericsson (Publ) Channel estimation and equalization for hard-limited signals
US8259864B2 (en) * 2009-02-06 2012-09-04 Qualcomm Incorporated Methods and systems for fourier-quadratic basis channel estimation in OFDMA systems

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
None

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9450786B2 (en) 2014-03-27 2016-09-20 King Fahd University Of Petroleum And Minerals Low-complexity method for estimating impulse-radio UWB wireless channels

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EP2446596A2 (fr) 2012-05-02
CN102804719B (zh) 2015-06-03
US20100322357A1 (en) 2010-12-23
WO2010150198A3 (fr) 2011-02-24
CN102804719A (zh) 2012-11-28
EP2446596B1 (fr) 2017-08-09
US8379773B2 (en) 2013-02-19

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